Advances in computing technologies enable a variety of computing systems to leverage digital visual representations of users. By way of example, these visual representations are used as user profile pictures, as user likenesses in digital communications (e.g., SMS text messages, instant messages) or animated as virtual guides through virtual environments, as backgrounds displayed based on a current device mode (e.g., home page, sleep screen), and so on. Many of these computing systems include functionality that supports user interaction to generate an “avatar,” a virtual representation of a user. Alternately or in addition, these computing systems include functionality that supports using digital visual content (e.g., an image) depicting an avatar.
Many conventional avatar generation systems present different, cartoon versions of body-part features (e.g., a face shape, hair, eyes, nose, mouth, wrinkles, general build, height, and so on), which are user selectable to build an avatar. A drawback of these systems, though, is that the selection process—to select a corresponding version of each selectable feature—can be tedious for client device users. Moreover, users may not accurately select the cartoon versions of the features that best preserve their identity or expression. Other conventional avatar generation systems leverage machine-learning models that convert a photorealistic image of person into an image depicting a cartoonized avatar. However, these conventionally-configured systems also have drawbacks. For example, such systems are limited to producing images of avatars in cartoon styles which the systems depend on being more photorealistic to produce higher quality avatar images. With less photorealistic cartoon styles, these conventionally-configured systems fail to reliably preserve identities and expressions of depicted persons and also suffer from quality issues, e.g. they produce grainy images of the cartoonized avatars. Due to these drawbacks, client device users often opt for other forms of representation in digital content, such as digital photographs, digital images depicting something other than a likeness of a user (e.g., landscape, artwork, graphics), and so on.